Climate change mitigationClimate change mitigation is action to limit climate change by reducing emissions of greenhouse gases or removing those gases from the atmosphere. The recent rise in global average temperature is mostly due to emissions from burning fossil fuels such as coal, oil, and natural gas. Mitigation can reduce emissions by transitioning to sustainable energy sources, conserving energy, and increasing efficiency. It is possible to remove carbon dioxide () from the atmosphere by enlarging forests, restoring wetlands and using other natural and technical processes.
Water footprintA water footprint shows the extent of water use in relation to consumption by people. The water footprint of an individual, community, or business is defined as the total volume of fresh water used to produce the goods and services consumed by the individual or community or produced by the business. Water use is measured in water volume consumed (evaporated) and/or polluted per unit of time. A water footprint can be calculated for any well-defined group of consumers (e.g.
Carbon footprintThe carbon footprint (or greenhouse gas footprint) serves as an indicator to compare the total amount of greenhouse gases emitted from an activity, product, company or country. Carbon footprints are usually reported in tons of emissions (CO2-equivalent) per unit of comparison; such as per year, person, kg protein, km travelled and alike. For a product, its carbon footprint includes the emissions for the entire life cycle from the production along the supply chain to its final consumption and disposal.
Statistical modelA statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, the data-generating process. When referring specifically to probabilities, the corresponding term is probabilistic model. A statistical model is usually specified as a mathematical relationship between one or more random variables and other non-random variables.
Politics of climate changeThe politics of climate change results from different perspectives on how to respond to climate change. Global warming is driven largely by the emissions of greenhouse gases due to human economic activity, especially the burning of fossil fuels, certain industries like cement and steel production, and land use for agriculture and forestry. Since the Industrial Revolution, fossil fuels have provided the main source of energy for economic and technological development.
Emission intensityLife-cycle greenhouse gas emissions of energy sources An emission intensity (also carbon intensity or C.I.) is the emission rate of a given pollutant relative to the intensity of a specific activity, or an industrial production process; for example grams of carbon dioxide released per megajoule of energy produced, or the ratio of greenhouse gas emissions produced to gross domestic product (GDP).
Greenhouse gas emissionsGreenhouse gas emissions (abbreviated as GHG emissions) from human activities strengthen the greenhouse effect, contributing to climate change. Carbon dioxide (), from burning fossil fuels such as coal, oil, and natural gas, is one of the most important factors in causing climate change. The largest emitters are China followed by the US, although the United States has higher emissions per capita. The main producers fueling the emissions globally are large oil and gas companies.
Statistical model validationIn statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences from models that appear to fit their data may be flukes, resulting in a misunderstanding by researchers of the actual relevance of their model. To combat this, model validation is used to test whether a statistical model can hold up to permutations in the data.
Statistical model specificationIn statistics, model specification is part of the process of building a statistical model: specification consists of selecting an appropriate functional form for the model and choosing which variables to include. For example, given personal income together with years of schooling and on-the-job experience , we might specify a functional relationship as follows: where is the unexplained error term that is supposed to comprise independent and identically distributed Gaussian variables.
Climate change scenarioClimate change scenarios or socioeconomic scenarios are projections of future greenhouse gas (GHG) emissions used by analysts to assess future vulnerability to climate change. Scenarios and pathways are created by scientists to survey any long term routes and explore the effectiveness of mitigation and helps us understand what the future may hold this will allow us to envision the future of human environment system. Producing scenarios requires estimates of future population levels, economic activity, the structure of governance, social values, and patterns of technological change.
Individual action on climate changeIndividual action on climate change can include personal choices in many areas, such as diet, travel, household energy use, consumption of goods and services, and family size. Individuals can also engage in local and political advocacy around issues of climate change. People who wish to reduce their carbon footprint (particularly those in high income countries with high consumption lifestyles), can take "high-impact" actions, such as avoiding frequent flying and petrol fuelled cars, eating mainly a plant-based diet, having fewer children, using clothes and electrical products for longer, and electrifying homes.
Ecological footprintThe ecological footprint is a method promoted by the Global Footprint Network to measure human demand on natural capital, i.e. the quantity of nature it takes to support people and their economies. It tracks this demand through an ecological accounting system. The accounts contrast the biologically productive area people use for their consumption to the biologically productive area available within a region, nation, or the world (biocapacity, the productive area that can regenerate what people demand from nature).
Model selectionModel selection is the task of selecting a model from among various candidates on the basis of performance criterion to choose the best one. In the context of learning, this may be the selection of a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is well-suited to the problem of model selection.
Public opinion on climate changePublic opinion on climate change is the aggregate of attitudes or beliefs held by a population concerning issues relating to "anthropogenic climate change, perceptions of climate change risks, concern about its seriousness, and thoughts on what, if anything, should be done to address it." Public opinion on climate change is related to a broad set of variables, including the effects of sociodemographic, political, cultural, economic, and environmental factors" as well as media coverage and interaction with different news and social media.
Climate resilienceClimate resilience is defined as the "capacity of social, economic and ecosystems to cope with a hazardous event or trend or disturbance". This is done by "responding or reorganising in ways that maintain their essential function, identity and structure (as well as biodiversity in case of ecosystems) while also maintaining the capacity for adaptation, learning and transformation". The key focus of increasing climate resilience is to reduce the climate vulnerability that communities, states, and countries currently have with regards to the many effects of climate change.
Statistical inferenceStatistical inference is the process of using data analysis to infer properties of an underlying distribution of probability. Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population.
Global warming potentialGlobal warming potential (GWP) is a measure of how much infrared thermal radiation a greenhouse gas added to the atmosphere would absorb over a given time frame, as a multiple of the radiation that would be absorbed by the same mass of added carbon dioxide (). GWP is 1 for . For other gases it depends on how strongly the gas absorbs infrared thermal radiation, how quickly the gas leaves the atmosphere, and the time frame being considered. The carbon dioxide equivalent (e or eq or -e) is calculated from GWP.
Low-carbon dietA low-carbon diet is a diet with low greenhouse gas emissions. Choosing a low carbon diet is one facet of developing sustainable diets which increase the long-term sustainability of humanity. It is estimated that the food system is responsible for a quarter to a third of human-caused greenhouse gas emissions. Major tenets of a low-carbon diet include eating a plant-based diet, and in particular little or no beef and dairy. A 2014 study into the real-life diets of British people estimated their greenhouse gas footprints in terms of kilograms of carbon dioxide equivalent per day: 7.
Linear modelIn statistics, the term linear model is used in different ways according to the context. The most common occurrence is in connection with regression models and the term is often taken as synonymous with linear regression model. However, the term is also used in time series analysis with a different meaning. In each case, the designation "linear" is used to identify a subclass of models for which substantial reduction in the complexity of the related statistical theory is possible.
Active learningActive learning is "a method of learning in which students are actively or experientially involved in the learning process and where there are different levels of active learning, depending on student involvement." states that "students participate [in active learning] when they are doing something besides passively listening." According to Hanson and Moser (2003) using active teaching techniques in the classroom can create better academic outcomes for students.
